在无缝I-II期临床试验中将细胞毒性药物与连续剂量水平相结合。

IF 1 4区 数学 Q3 STATISTICS & PROBABILITY
José L. Jiménez, Mourad Tighiouart
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引用次数: 4

摘要

癌症I-II期临床试验设计旨在加速药物开发。在短期内无法确定疗效的情况下,通常将研究分为两个阶段:i)第一阶段,仅根据毒性数据增加剂量,我们寻找最大耐受剂量(MTD)集;ii)第二阶段,我们在MTD集中寻找最有效的剂量。在连续剂量水平领域,目前可用的方法包括在第一阶段后固定MTD,并丢弃所有收集的第一阶段疗效数据。然而,当跨阶段存在独特的患者群体时,这种方法显然效率低下。在这篇文章中,我们提出了两种细胞毒性药物组合的两阶段设计,假设整个研究中只有一个患者群体。在第一阶段,使用过量控制条件升级(EWOC)来分配连续的患者队列。在第二阶段,我们采用自适应随机化方法,沿着不断更新的估计MTD曲线将患者分配到药物组合中。在实际案例研究的背景下,通过广泛的模拟对所提出的方法进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combining cytotoxic agents with continuous dose levels in seamless phase I-II clinical trials

Phase I-II cancer clinical trial designs are intended to accelerate drug development. In cases where efficacy cannot be ascertained in a short period of time, it is common to divide the study in two stages: (i) a first stage in which dose is escalated based only on toxicity data and we look for the maximum tolerated dose (MTD) set and (ii) a second stage in which we search for the most efficacious dose within the MTD set. Current available approaches in the area of continuous dose levels involve fixing the MTD after stage I and discarding all collected stage I efficacy data. However, this methodology is clearly inefficient when there is a unique patient population present across stages. In this article, we propose a two-stage design for the combination of two cytotoxic agents assuming a single patient population across the entire study. In stage I, conditional escalation with overdose control is used to allocate successive cohorts of patients. In stage II, we employ an adaptive randomisation approach to allocate patients to drug combinations along the estimated MTD curve, which is constantly updated. The proposed methodology is assessed with extensive simulations in the context of a real case study.

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来源期刊
CiteScore
2.50
自引率
0.00%
发文量
76
审稿时长
>12 weeks
期刊介绍: The Journal of the Royal Statistical Society, Series C (Applied Statistics) is a journal of international repute for statisticians both inside and outside the academic world. The journal is concerned with papers which deal with novel solutions to real life statistical problems by adapting or developing methodology, or by demonstrating the proper application of new or existing statistical methods to them. At their heart therefore the papers in the journal are motivated by examples and statistical data of all kinds. The subject-matter covers the whole range of inter-disciplinary fields, e.g. applications in agriculture, genetics, industry, medicine and the physical sciences, and papers on design issues (e.g. in relation to experiments, surveys or observational studies). A deep understanding of statistical methodology is not necessary to appreciate the content. Although papers describing developments in statistical computing driven by practical examples are within its scope, the journal is not concerned with simply numerical illustrations or simulation studies. The emphasis of Series C is on case-studies of statistical analyses in practice.
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